1
Development of machine learning algorithms for the precise and effective evaluation of field conditions
Action and
impementation of the project
The implementation of irisTECH system was developed with the following steps:
2
Development of software for the visualization and storage of data
Expected Results
Time Savings (+30%)
With real time control of the fertilizer hopperμε έλεγχο γραμμικού λιπασματοδιανομέα σε πραγματικό χρόνο
Increased Precision (+15%)
Due to the application of A.I. algorithmsβάση της αξιοποίησης αλγορίθμων τεχνητής νοημοσύνης
Increase in Quality
Of the cotton fiber due to better and more uniform farm production
Decrease of production cost
Due to lower use of fertilizer inputs
Increase of smart farming machines (15%)
In farming activities
Increase of production(15%)
Based on the better allocation of fertilizer in rows
Economic development of the agri-food sector
Due to the restructuring and modernization of farms
Savings on Fertilizer (-20%)
Increasing the financial efficiency of cotton farmers
This project is implemented under the framework RESEARCH-CREATE-INNOVATE and is co-funded by the European Regional Development Fund of the European Union and national funds via the research program Competitiveness, Entrepreneurship & Innovation (research program number: Τ2ΕΔΚ-02936)
Integrated system of application of differentiated fertilization with the use of an innovative system of artificial intelligence in linear crops.
Useful
STATEMENTS
Copyright @ 2023 AGROMET. Designed by adviser